Premise Blog

Product news, stories, and occasional updates.

Mobile Devices and The Inversion of Control

The rise of internet-enabled mobile devices is rapidly changing our ability to measure and report on aggregate human activity and is enabling bottom-up, collaborative cartography of economic, social and political microstructure at a previously unprecedented scale. This trend has far-reaching consequences for countries where such incumbent structures are barriers to development: Monopolistic price setters, local service corruption, and institutionalized bribery all present clear obstacles “the adoption of policies that would reduce market failure” [Acemoğlu; 2012]. However, these locally inefficient power structures are coming under increasing scrutiny due to the rapid rise of the mobile internet Panopticon.

Written By
JOE REISINGER

Instability in Asian Inflation

All through the summer and well into the fall, the data science teams at Premise have seen Asian economies struggle with inflation — though if you’ve been looking only at the headline numbers, you might have missed it. As recently as this past week, the National Bureau of Statistics of China reported that consumer prices rose 0.1 percent month-over-month, underperforming economists’ predictions of a 0.2 percent increase. A modest number, to be sure, but one that tells only part of the story: since early July, the teams at Premise have seen vegetable prices in China rising at a rapid clip.

Written By
Kiran Gollakota

Introducing Premise

Multinational corporations, governments, NGOs, Central Banks, trading houses… every year these organizations spend billions of dollars in pursuit of econometric and human development data and statistics. The reality is that the quantity of information gathered is rather small, the quality can vary, and the latency is very high. Is it any wonder that conditions on the ground zig while headline indicators zag? Who can fault policy makers or consumer good companies or trading houses or relief agencies for basing decisions on out-of-date and lumpy data?

Written By
David Soloff

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